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Advanced Elasticsearch 7.0

Advanced Elasticsearch 7.0

By : Wong
3.5 (4)
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Advanced Elasticsearch 7.0

Advanced Elasticsearch 7.0

3.5 (4)
By: Wong

Overview of this book

Building enterprise-grade distributed applications and executing systematic search operations call for a strong understanding of Elasticsearch and expertise in using its core APIs and latest features. This book will help you master the advanced functionalities of Elasticsearch and understand how you can develop a sophisticated, real-time search engine confidently. In addition to this, you'll also learn to run machine learning jobs in Elasticsearch to speed up routine tasks. You'll get started by learning to use Elasticsearch features on Hadoop and Spark and make search results faster, thereby improving the speed of query results and enhancing the customer experience. You'll then get up to speed with performing analytics by building a metrics pipeline, defining queries, and using Kibana for intuitive visualizations that help provide decision-makers with better insights. The book will later guide you through using Logstash with examples to collect, parse, and enrich logs before indexing them in Elasticsearch. By the end of this book, you will have comprehensive knowledge of advanced topics such as Apache Spark support, machine learning using Elasticsearch and scikit-learn, and real-time analytics, along with the expertise you need to increase business productivity, perform analytics, and get the very best out of Elasticsearch.
Table of Contents (25 chapters)
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1
Section 1: Fundamentals and Core APIs
8
Section 2: Data Modeling, Aggregations Framework, Pipeline, and Data Analytics
13
Section 3: Programming with the Elasticsearch Client
16
Section 4: Elastic Stack
20
Section 5: Advanced Features

Overview of the Elasticsearch Python client

Elasticsearch provides two types of clients for Python. The elasticsearch-py package provides an official low-level client. The elasticsearch-dsl-py package provides a high-level library that is built on top of the low-level client. The high-level library provides a more convenient way for you to manipulate queries since it is close to the Elasticsearch JSON DSL. Both clients support versions from 2.x to 7.x. Assuming that you have a working environment for Python 3.6, use the following step-by-step instructions:

  1. To install the Python Elasticsearch client, you can use the pip command, as shown in the following code block:
pip install elasticsearch==7.0.0
  1. To install the Python Elasticsearch DSL high-level library, you can refer to the following code block:
pip install elasticsearch-dsl==7.0.0
  1. If you are working on a project, the...

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